Sergio E. Baranzini is Distinguished Professor of Neurology I at the University of California San
Francisco (UCSF). He is also a member of the Graduate Program in Bioinformatics, the Institute for
Human Genetics, the Bakar Computational Health Sciences Institute, ImmunoX, and the California
Institute for Quantitative Biology (QB3). He holds the Heidrich Friends and Family endowed chair in
Neurology. Dr. Baranzini earned his degrees in clinical biochemistry (1992) and PhD in human molecular
Ebru is an assistant specialist at the Baranzini Laboratory - Department of Neurology. She completed her master’s degree in computer and information science from the City University of New York. She worked as a data scientist intern at Stanford University - Radiology Department and as a data a scientist in various MedTech startups. She is currenty involved in SPOKE development. Her main focuses are machine learning, graph theory, and database integration.
Joseph is a Reseach Associate/Lab Manager of the International Multiple Sclorosis Microbiome Study with the Baranzini Lab. As a proud San Francisco native, they decided to use their educational background in neurodevelopmental disability and neurodegenerative diseases to contribute to the meaningful research done at UCSF. Their tasks involve conducting DNA isolation and purification from participants around the globe, as well as assisting in the Sandler Gnotobiotic Animal Facility.
Gianmarco is an Italian Medical Doctor whose clinical and research interests have centered on Multiple Sclerosis (MS) since the early stages of his medical training. During his Neurology residency in Rome, he deepened his focus on unraveling the clinical and pathobiological complexities of MS. His work integrates genetic and phenotypic insights, employing big data through SPOKE and AI-driven models to advance precision medicine in MS.
Gabriel is an Argentinian Medical Doctor. He earned his medical degree from Universidad Nacional de La Plata. He is a self taught programmer, data scientist, and machine learning practitioner. He is currently involved in SPOKE development. His research interests lies in the integration of data science with clinical practice.
Hope is a Clinical Research Coordinator for the International Multiple Sclerosis Microbiome Study at the Baranzini Laboratory. Being born at UCSF, she felt a strong connection to the institution and knew it was the perfect place for her to dedicate her learnings and passions. After earning her BS in Business Administration from San Francisco State University, she discovered her passion for helping others.
Wanjun is a doctoral student in the Biological and Medical Informatics (BMI) program at the University of California, San Francisco (UCSF). He earned a dual degree in Chemical Engineering (B.S.) and Economics (B.A.) from the University of California, San Diego, and has a diverse research background in physiology, genetics, and epidemiology. His research interests focus on leveraging biological knowledge networks and multi-omics data to enhance our understanding of disease mechanisms and evolutionary processes.
Shaobo Ma is an associate specialist in the Baranzini laboratory and works with the Baranzini laboratory to explore the effect of gut microbes on the immune system and nervous system in multiple sclerosis. He is a PhD student in nutrition at Northwest A&F University, China.
Maura is a Neuroscience PhD student from UC Berkeley studying the mechanisms behind the gut-brain axis in multiple sclerosis with the Baranzini Lab. Born and raised in Chicago, Maura attended the University of Wisconsin-Madison and graduated with a B.S. in Biomedical Engineering with a double major in Communication Arts (Radio/TV/Film) in May 2020. They bring from the Midwest a passion for in vitro modeling of mammalian systems and community-led efforts to support better brain health.
Karthik Soman currently works as a Specialist in Baranzini lab. His work mainly focuses on building knowledge network by data integration, graph data science (such as knowledge embedding), machine learning and applying them on clinical and biological data for disease prediction in an explainable fashion using network insights. To achieve this, he leverages a combination of graph data and big data analytics, employing High Performance Computing clusters to advance precision medicine.
Catalina Villouta is an Associate Specialist at the Baranzini Laboratory, specializing in SPOKE’s development and algorithmic uses. Leveraging graph theory and machine learning, Catalina helps to advance SPOKE in the domain of precision medicine. With a Master’s in Chemical Engineering from UC Berkeley and industry experience at Gilead Sciences, Catalina brings a unique blend of analytical skills and expertise.
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